Paper Citation Record · LEDGER

Implicit Gradient Regularization

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2009.11162.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2009.11162 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:17:24.914556Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-09T07:56:04.666556Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6cca0cfc-513f-4017-8289-3552e2163051 · inbound

Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization cites this paper.

Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization Implicit Gradient Regularization

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T17:03:52.513130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98b1bf19-32b7-4d81-bbfd-a24df0b006b0 · inbound

CGD: Modifying the Loss Landscape by Gradient Regularization cites this paper.

CGD: Modifying the Loss Landscape by Gradient Regularization Implicit Gradient Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:24.914556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e10bec04-7f0f-4a15-9eab-f4feff0a122d · inbound

Neural Thermodynamic Laws for Large Language Model Training cites this paper.

Neural Thermodynamic Laws for Large Language Model Training Implicit Gradient Regularization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T21:16:10.333148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 469237c1-e7b6-4730-92df-245978afd23e · inbound

Optimizers Qualitatively Alter Solutions And We Should Leverage This cites this paper.

Optimizers Qualitatively Alter Solutions And We Should Leverage This Implicit Gradient Regularization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T16:56:21.496667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb2fe723-d15c-4539-8965-aa09ce56a16a · inbound

What Can Grokking Teach Us About Learning Under Nonstationarity? cites this paper.

What Can Grokking Teach Us About Learning Under Nonstationarity? Implicit Gradient Regularization

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-15T17:59:10.285588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04dab5ab-e099-40d9-89bd-d58df15439aa · inbound

Design Criteria for SGD Preconditioners: Local Conditioning, Noise Floors, and Basin Stability cites this paper.

Design Criteria for SGD Preconditioners: Local Conditioning, Noise Floors, and Basin Stability Implicit Gradient Regularization

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T20:34:06.470659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c7bd95d-0f58-4987-a60e-a24c70d227f5 · inbound

Quantitative Understanding of PDF Fits and their Uncertainties cites this paper.

Quantitative Understanding of PDF Fits and their Uncertainties Implicit Gradient Regularization

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T13:34:53.600453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a05221e9-d411-49e0-9c35-45d62f927d3e · inbound

Gradient Regularization Mitigates Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards cites this paper.

Gradient Regularization Mitigates Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards Implicit Gradient Regularization

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-02T22:07:35.968094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea6b6bd2-b629-4d66-ae83-45f441ac7412 · inbound

Towards Universal Convergence of Backward Error in Linear System Solvers cites this paper.

Towards Universal Convergence of Backward Error in Linear System Solvers Implicit Gradient Regularization

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:12:26.571953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4ae70446-ac18-413c-8435-4ce4945db4d3 · inbound

Towards Universal Convergence of Backward Error in Linear System Solvers cites this paper.

Towards Universal Convergence of Backward Error in Linear System Solvers Implicit Gradient Regularization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-12T19:27:25.263608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2629edd3-80b4-49bf-ab02-137d4254f6da · inbound

Estimating Implicit Regularization in Deep Learning cites this paper.

Estimating Implicit Regularization in Deep Learning Implicit Gradient Regularization

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:26:13.017392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cee82c61-9b1c-4e05-841b-519fd79edc41 · inbound

Characterizing and Correcting Effective Target Shift in Online Learning cites this paper.

Characterizing and Correcting Effective Target Shift in Online Learning Implicit Gradient Regularization

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:40:53.807364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3152b507-0779-4e32-82ad-fa339ef32253 · inbound

Thermodynamic Irreversibility of Training Algorithms cites this paper.

Thermodynamic Irreversibility of Training Algorithms Implicit Gradient Regularization

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-22T04:41:04.218335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 971d236a-4ee7-4b8e-84cb-10659b71125c · inbound

How Optimality Structures Sparse Dictionaries: A Theory for Understanding SAE Representations cites this paper.

How Optimality Structures Sparse Dictionaries: A Theory for Understanding SAE Representations Implicit Gradient Regularization

Reference 127

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T01:46:26.180124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e1a573e6-dac5-45a6-8920-3d8b9eb9f194 · inbound

Second-Order Path Kernel Interpolation Formulas in Machine Learning cites this paper.

Second-Order Path Kernel Interpolation Formulas in Machine Learning Implicit Gradient Regularization

Reference 152

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T16:47:10.361501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 13a74d37-dce6-41b5-bb7a-b447c6107416 · inbound

Some Inverse Problems in Particle Physics cites this paper.

Some Inverse Problems in Particle Physics Implicit Gradient Regularization

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:47:26.163993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ca93cfe1-a664-42fc-ad3d-0ad2e0a99b4d · inbound

Avoiding unsafe sets when training with Langevin Dynamics cites this paper.

Avoiding unsafe sets when training with Langevin Dynamics Implicit Gradient Regularization

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-07-09T07:56:04.667484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4ccc6b35-4493-4cfb-ae32-da9827f9ae39 · inbound

Avoiding unsafe sets when training with Langevin Dynamics cites this paper.

Avoiding unsafe sets when training with Langevin Dynamics Implicit Gradient Regularization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T08:08:39.953079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04dc6d74-d55d-4e0d-a757-e2410cf8dc95 · inbound

Information Abundance Paradox: Long-Context Training Undermines Parametric Knowledge cites this paper.

Information Abundance Paradox: Long-Context Training Undermines Parametric Knowledge Implicit Gradient Regularization

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T00:19:14.499066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.